C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2164: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_'+mat+'_'+self.name+'_'+scen] = self.scenario[scen].material[mat].matdataOut_m[keywd]
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2166: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
USyearly[nicekey+'_Module_'+self.name+'_'+scen] = USyearly[filter_col].sum(axis=1)
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2255: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
scende_demands.loc[:,colname] = scende_demands.sum(axis=1) #sums module and material energy demands
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2255: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
scende_demands.loc[:,colname] = scende_demands.sum(axis=1) #sums module and material energy demands
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2255: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
scende_demands.loc[:,colname] = scende_demands.sum(axis=1) #sums module and material energy demands
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2255: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
scende_demands.loc[:,colname] = scende_demands.sum(axis=1) #sums module and material energy demands
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2255: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
scende_demands.loc[:,colname] = scende_demands.sum(axis=1) #sums module and material energy demands
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2255: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
scende_demands.loc[:,colname] = scende_demands.sum(axis=1) #sums module and material energy demands
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2255: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
scende_demands.loc[:,colname] = scende_demands.sum(axis=1) #sums module and material energy demands
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2255: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
scende_demands.loc[:,colname] = scende_demands.sum(axis=1) #sums module and material energy demands
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2255: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
scende_demands.loc[:,colname] = scende_demands.sum(axis=1) #sums module and material energy demands
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2255: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
scende_demands.loc[:,colname] = scende_demands.sum(axis=1) #sums module and material energy demands
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2255: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
scende_demands.loc[:,colname] = scende_demands.sum(axis=1) #sums module and material energy demands
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2255: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
scende_demands.loc[:,colname] = scende_demands.sum(axis=1) #sums module and material energy demands
C:\Users\hmirletz\Documents\GitHub\PV_ICE\PV_ICE\main.py:2255: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
scende_demands.loc[:,colname] = scende_demands.sum(axis=1) #sums module and material energy demands
